Automatic speech recognition using articulatory features from subject-independent acoustic-to-articulatory inversion

An automatic speech recognition approach is presented which uses articulatory features estimated by a subject-independent acoustic-to-articulatory inversion. The inversion allows estimation of articulatory features from any talker's speech acoustics using only an exemplary subject's articu...

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Bibliographic Details
Published inThe Journal of the Acoustical Society of America Vol. 130; no. 4; pp. EL251 - EL257
Main Authors Ghosh, Prasanta Kumar, Narayanan, Shrikanth
Format Journal Article
LanguageEnglish
Published Melville, NY Acoustical Society of America 01.10.2011
American Institute of Physics
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Summary:An automatic speech recognition approach is presented which uses articulatory features estimated by a subject-independent acoustic-to-articulatory inversion. The inversion allows estimation of articulatory features from any talker's speech acoustics using only an exemplary subject's articulatory-to-acoustic map. Results are reported on a broad class phonetic classification experiment on speech from English talkers using data from three distinct English talkers as exemplars for inversion. Results indicate that the inclusion of the articulatory information improves classification accuracy but the improvement is more significant when the speaking style of the exemplar and the talker are matched compared to when they are mismatched.
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ISSN:0001-4966
1520-8524
1520-8524
DOI:10.1121/1.3634122